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I will not be able to answer this question. Others might. <br />
The chance to get an answer might be higher if you mention from which library precision_score is coming from.<br />
<br />
Perhaps you add the statement that imports precision_score to your question and you add the module containing precision score to your question's title?
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Simon Leung

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Any idea how the follow result is calculated :<br />
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Testlabels3 &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; = ['Red', 'Green', 'Green', 'Red', 'Yellow']<br />
PredictedLabels3 = ['Red', 'Red', 'Green', 'Yellow', 'Yellow'] <br />
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precision_score(TestLabels<wbr />3, PredictedLabels3, average=None)<br />
result : array([1. , 0.5, 0.5])<br />
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precision_score(TestLabels<wbr />3, PredictedLabels3, average='weighted')<br />
result : 0.7
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Any idea how the follow result is calculated :

Testlabels3           = ['Red', 'Green', 'Green', 'Red', 'Yellow']
PredictedLabels3 = ['Red', 'Red', 'Green', 'Yellow', 'Yellow'] 

precision_score(TestLabels3, PredictedLabels3, average=None)
result : array([1. , 0.5, 0.5])

precision_score(TestLabels3, PredictedLabels3, average='weighted')
result : 0.7

Precision Score in Python

Statistical packages are software titles, such as JMP and GNU Octave, and programming languages, such as MATLAB, R and SAS, that are used to discover, explore and analyze data and suggest useful conclusions, either to learn something unexpected or to confirm a hypothesis. The field includes the design and analysis of techniques to give approximate but accurate solutions to hard problems in statistics, econometrics, time-series, optimization and 2D- and 3D-visualization. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, in different business, science, and social science domains.

Statistical Packages

Python is a widely used general-purpose, high-level programming language. Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in other languages. Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive set of standard libraries, including NumPy, SciPy, Django, PyQuery, and PyLibrary.